When buyers ask AI which business software to buy, who gets named?
We put 100 real software-buyer questions to ChatGPT and Gemini and Perplexity and checked which of 24 B2B SaaS vendors each answer named. 5 of the 100 questions got no named vendor at all — spanning CRM, HR, ERP, project management, marketing automation and customer support, the everyday categories a business software buyer actually shops in. Run the check for your product →
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Why we ran this
B2B software buying has quietly moved from "search and compare ten review sites" to "ask an assistant and act on the shortlist it gives you." That shortlist is assembled from whatever content the assistant can find — vendor sites, review platforms, comparison blogs, community forums — and it either names specific products or it doesn’t. This benchmark reads how visible B2B SaaS vendors currently are across the categories a real buyer shops in, engine by engine, and where the biggest content openings are.
How we measured it
We wrote 100 questions in the language a real business software buyer actually uses — category comparisons, pricing and ROI, security and compliance, implementation and integration, switching and alternatives, and buyer-segment fit (all 100 are explorable in full below). Each question was sampled once per engine, and every answer was checked for a mention of any of 24 identifiable B2B SaaS vendors — from broad platform suites like Salesforce and Workday to focused point solutions like Notion and Gusto — using the same name matcher a live Inserviss scan uses.
A single pass per engine establishes direction and priority; it is not a trend line. Citations are reported as measured; query volumes are labelled estimates, shown as ranges. Engines are never blended. This run covers ChatGPT and Gemini and Perplexity; Microsoft Copilot is not currently sampled.
The tracked list covers 24 vendors a real buyer would plausibly shortlist across CRM, HR, ERP, project management, marketing automation and customer support — a deliberately broad, category-spanning set rather than one narrow product line.
What we found, at a glance
- Visibility varies sharply by engine. ChatGPT named a tracked vendor in 82 of 100 answers, Gemini named a tracked vendor in 95 of 100 answers and Perplexity named a tracked vendor in 83 of 100 answers.
- 5 of 100 questions got no tracked vendor on any engine.
- Salesforce is the most-named vendor, appearing in 91 of 300 answers. Every one of the 24 tracked vendors was named at least once.
- Platform suites and focused point solutions get named at very different rates. See the full breakdown, and which archetype AI actually favors, in the table below.
How often does AI name a vendor at all?
Below is the share of the 100 answers that named at least one tracked vendor, per engine — then the full table, every vendor against every engine, sortable by any column.
Share of 100 answers naming at least one of the 24 tracked vendors. Per engine, never blended.
| Vendor | ChatGPT | Gemini | Perplexity |
|---|---|---|---|
| Salesforcesuite | 27 | 42 | 22 |
| HubSpotsuite | 25 | 36 | 27 |
| Zohosuite | 16 | 26 | 26 |
| Microsoft Dynamics 365suite | 17 | 24 | 14 |
| Monday.com | 17 | 20 | 18 |
| Atlassian | 11 | 23 | 13 |
| SAPsuite | 11 | 22 | 12 |
| Asana | 13 | 16 | 13 |
| Slack | 6 | 25 | 5 |
| Workdaysuite | 8 | 18 | 7 |
| Pipedrive | 7 | 15 | 11 |
| Rippling | 8 | 16 | 5 |
| Notion | 7 | 15 | 6 |
| Freshworks | 6 | 10 | 11 |
| NetSuitesuite | 9 | 10 | 7 |
| BambooHR | 7 | 7 | 7 |
| Zendesk | 5 | 6 | 8 |
| Gusto | 6 | 7 | 5 |
| DocuSign | 4 | 9 | 4 |
| Smartsheet | 6 | 7 | 3 |
| Greenhouse | 4 | 6 | 5 |
| Airtable | 2 | 5 | 2 |
| ServiceNowsuite | 1 | 4 | 0 |
| Klaviyo | 2 | 2 | 0 |
Mentions across 100 answers per engine. Select a column heading to re-sort. Scroll the table sideways on a narrow screen.
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Where the openings are
Coverage varies by question type. Below is the best engine’s coverage for each cluster, out of ~17 questions.
Answers naming a vendor on the strongest engine, per cluster (out of ~17).
How this is estimated
Estimate — a range, not a keyword-tool export. Illustrative estimate, not a keyword-tool export. Each cluster has ~16-17 seed buyer questions; B2B SaaS is a broad, high-volume commercial category — long-tail intent phrases run ~150–600 monthly searches each globally, one or two head terms (e.g. "best CRM software") add ~4,000–14,000/mo, and an AI-assistant reformulation multiplier of ×2–4 accounts for the wider phrasing people use with an assistant. Ranges are rounded and widened. For a specific vendor, the real number comes from the check, not this table.
| Cluster | Best-engine coverage | Est. questions / mo |
|---|---|---|
| Category-Leader Comparisons | 17/17 | 22,000–78,000 |
| Pricing, ROI & Total Cost of Ownership | 15/17 | 9,000–34,000 |
| Security, Compliance & Data Governance | 16/17 | 5,500–21,000 |
| Implementation, Migration & Integration | 15/17 | 7,000–27,000 |
| Switching & Alternatives | 16/16 | 14,000–52,000 |
| Buyer-Segment Fit | 16/16 | 8,500–32,000 |
Volumes are an estimate, shown as a range. Illustrative estimate, not a keyword-tool export. Each cluster has ~16-17 seed buyer questions; B2B SaaS is a broad, high-volume commercial category — long-tail intent phrases run ~150–600 monthly searches each globally, one or two head terms (e.g. "best CRM software") add ~4,000–14,000/mo, and an AI-assistant reformulation multiplier of ×2–4 accounts for the wider phrasing people use with an assistant. Ranges are rounded and widened. For a specific vendor, the real number comes from the check, not this table.
The check runs this same 100-question universe against your product’s name, per engine, and returns your AI Visibility Score plus the exact questions where a competitor — or no one — is being named.
Check your product’s AI visibility →Explore the 100 questions
Every question, and exactly what each engine did with it — which vendors it named, and which sources it pulled from. Filter by cluster, search for your own name, or show only the questions no vendor has claimed.
The 5 questions no tracked vendor owns on any engine, with the sources AI cites instead — a ready-made content brief.
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Where each engine gets its answers
The domains each engine actually pulled from, per engine — never blended. ChatGPT splits its citations between vendor-owned pages (hubspot.com, salesforce.com, microsoft.com) and review platforms (G2, Capterra). Perplexity leans hardest on Forbes and Reddit, then review/comparison sites (G2, TechnologyAdvice) and how-to blogs (Zapier, The Digital Project Manager) — general web content, not vendor sites. Gemini names a tracked vendor in the most answers of the three (95 of 100), but its citations are the flattest and most fragmented — no domain appears more than twice across all 100 answers, a long tail of small comparison and review sites rather than a handful of dominant sources.
Times a domain was cited across the 100 answers. Blue = a tracked vendor’s own site.
About this study
- Single pass per engine. One sample per question per engine establishes direction; it does not average out run-to-run answer variance.
- Snapshot in time. Collected September 14, 2026. AI engines change their answers week to week; this is not a trend line.
- Conservative name matching. Short one-token vendor names (Slack, Notion, Gusto…) require an exact whole-word match, so a slight undercount is possible — but it cannot explain a 5-of-100 gap.
- ChatGPT and Gemini and Perplexity this run. Microsoft Copilot is not currently sampled; the measurement is identical when it is.
How to cite this study
To request the underlying data or discuss a vendor-specific analysis, contact igor@inserviss.app.
The same measurement, run against your product’s name — per engine, question by question — with your score and the questions to claim first.
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